Prosperity, War, Immigration, and "Cultural" Factors in Modeling United States Population Growth Since 1790
The growth of the United States population since 1790 can be modeled in terms of a nonlinear differential equation with time-dependent coefficients. The growth process represented by the model is subject to the effects of immigration, war, prosperity, and a so-called "cultural" factor. Spe...
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description | The growth of the United States population since 1790 can be modeled in terms of a nonlinear differential equation with time-dependent coefficients. The growth process represented by the model is subject to the effects of immigration, war, prosperity, and a so-called "cultural" factor. Specifically, the equation assumes that the rate of growth for a particular year is the result of positive factors' working against limiting factors. The positive factors comprise (1) a term proportional to the population size, p, for that particular year, and (2) a term equal to the immigrant population, p m ', for the same year. The limiting factors are all proportional to the square of the present population size, p 2 and comprise a war term, w, that aids the growth-limiting process; a prosperity term, ε g ', that inhibits the limiting process; and a culture term C, that supports the limiting process, too. The term, w, is taken to be proportional to the wartime size of the country's armed forces, assuming that the war effects on population growth of a land faced with either the immediate prospect or the reality of armed conflict include both the casualties and the disruption of family life and planning of those directly involved. The term ε g ' is intended to be a measure of the general prosperity level. It is taken to be proportional to the ups and downs of the GNP, above or below a smooth trend line, the latter being found by curve-fitting a growth curve to the actual GNP data. Finally, the culture term, C, is assumed to vary with time, but not to be tied explicitly to known environmental, social, or other causes. It is probably connected to age distribution within the population, average age of partners of first marriages, number of children per woman of childbearing age, advances in medicine, the set of prevailing values, the trend of family planning, and so on. The time history of C emerging from the computer-based optimization of the model shows a downward trend. The use of the word "cultural" leaves something to be desired, since such phenomena as war, prosperity, and immigration excluded from C are nevertheless products of culture. With the analytical form of the differential equation describing population growth set up in this way, all proportionality constants (parameters) involved were determined by means of a digital computer and on the basis of an optimization process which utilized the actual data of population size p * over the period 1790-1965. The residua |
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D.</creator><creatorcontrib>Diamantides, N. D.</creatorcontrib><description>The growth of the United States population since 1790 can be modeled in terms of a nonlinear differential equation with time-dependent coefficients. The growth process represented by the model is subject to the effects of immigration, war, prosperity, and a so-called "cultural" factor. Specifically, the equation assumes that the rate of growth for a particular year is the result of positive factors' working against limiting factors. The positive factors comprise (1) a term proportional to the population size, p, for that particular year, and (2) a term equal to the immigrant population, p m ', for the same year. The limiting factors are all proportional to the square of the present population size, p 2 and comprise a war term, w, that aids the growth-limiting process; a prosperity term, ε g ', that inhibits the limiting process; and a culture term C, that supports the limiting process, too. The term, w, is taken to be proportional to the wartime size of the country's armed forces, assuming that the war effects on population growth of a land faced with either the immediate prospect or the reality of armed conflict include both the casualties and the disruption of family life and planning of those directly involved. The term ε g ' is intended to be a measure of the general prosperity level. It is taken to be proportional to the ups and downs of the GNP, above or below a smooth trend line, the latter being found by curve-fitting a growth curve to the actual GNP data. Finally, the culture term, C, is assumed to vary with time, but not to be tied explicitly to known environmental, social, or other causes. It is probably connected to age distribution within the population, average age of partners of first marriages, number of children per woman of childbearing age, advances in medicine, the set of prevailing values, the trend of family planning, and so on. The time history of C emerging from the computer-based optimization of the model shows a downward trend. The use of the word "cultural" leaves something to be desired, since such phenomena as war, prosperity, and immigration excluded from C are nevertheless products of culture. With the analytical form of the differential equation describing population growth set up in this way, all proportionality constants (parameters) involved were determined by means of a digital computer and on the basis of an optimization process which utilized the actual data of population size p * over the period 1790-1965. The residual (p * -p) of this optimization or curve-fitting process was further examined through its autocorrection function, for additional deterministic components which were not accounted for by the model up to this point. The auto-correlation function provides a measure of the dependence of the population size p * for any year upon past values of p * ; it has the distinct feature of lifting any regular pattern possibly present in the data above the level of random fluctuations. The autocorrelation function of the residual (p * -p) did indicate the presence of a periodic component with a period of about sixty-five years. Accordingly, a periodic term of the same period was included in the cultural factor C, and the model was reoptimized. This resulted in a substantial reduction of the residual. A similar probing of the prosperity term, ε g , indicates the presence of a period one-half as long.</description><identifier>ISSN: 0070-3370</identifier><identifier>EISSN: 1533-7790</identifier><identifier>DOI: 10.2307/2060209</identifier><language>eng</language><publisher>Chicago, Ill: The Population Association of America</publisher><subject>Autocorrelation ; Censuses ; Demography ; Differential equations ; Gross national product ; Parametric models ; Population growth ; Population size ; Sine function ; War</subject><ispartof>Demography, 1968-01, Vol.5 (1), p.268-305</ispartof><rights>Copyright 1968 Population Association of America</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c204t-11786adc9bcb7ecb2fae22a29eaa39f747e08e1452dd62f158d5d1f6d26625453</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/2060209$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/2060209$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,4009,27848,27902,27903,27904,57996,58229</link.rule.ids></links><search><creatorcontrib>Diamantides, N. D.</creatorcontrib><title>Prosperity, War, Immigration, and "Cultural" Factors in Modeling United States Population Growth Since 1790</title><title>Demography</title><description>The growth of the United States population since 1790 can be modeled in terms of a nonlinear differential equation with time-dependent coefficients. The growth process represented by the model is subject to the effects of immigration, war, prosperity, and a so-called "cultural" factor. Specifically, the equation assumes that the rate of growth for a particular year is the result of positive factors' working against limiting factors. The positive factors comprise (1) a term proportional to the population size, p, for that particular year, and (2) a term equal to the immigrant population, p m ', for the same year. The limiting factors are all proportional to the square of the present population size, p 2 and comprise a war term, w, that aids the growth-limiting process; a prosperity term, ε g ', that inhibits the limiting process; and a culture term C, that supports the limiting process, too. The term, w, is taken to be proportional to the wartime size of the country's armed forces, assuming that the war effects on population growth of a land faced with either the immediate prospect or the reality of armed conflict include both the casualties and the disruption of family life and planning of those directly involved. The term ε g ' is intended to be a measure of the general prosperity level. It is taken to be proportional to the ups and downs of the GNP, above or below a smooth trend line, the latter being found by curve-fitting a growth curve to the actual GNP data. Finally, the culture term, C, is assumed to vary with time, but not to be tied explicitly to known environmental, social, or other causes. It is probably connected to age distribution within the population, average age of partners of first marriages, number of children per woman of childbearing age, advances in medicine, the set of prevailing values, the trend of family planning, and so on. The time history of C emerging from the computer-based optimization of the model shows a downward trend. The use of the word "cultural" leaves something to be desired, since such phenomena as war, prosperity, and immigration excluded from C are nevertheless products of culture. With the analytical form of the differential equation describing population growth set up in this way, all proportionality constants (parameters) involved were determined by means of a digital computer and on the basis of an optimization process which utilized the actual data of population size p * over the period 1790-1965. The residual (p * -p) of this optimization or curve-fitting process was further examined through its autocorrection function, for additional deterministic components which were not accounted for by the model up to this point. The auto-correlation function provides a measure of the dependence of the population size p * for any year upon past values of p * ; it has the distinct feature of lifting any regular pattern possibly present in the data above the level of random fluctuations. The autocorrelation function of the residual (p * -p) did indicate the presence of a periodic component with a period of about sixty-five years. Accordingly, a periodic term of the same period was included in the cultural factor C, and the model was reoptimized. This resulted in a substantial reduction of the residual. A similar probing of the prosperity term, ε g , indicates the presence of a period one-half as long.</description><subject>Autocorrelation</subject><subject>Censuses</subject><subject>Demography</subject><subject>Differential equations</subject><subject>Gross national product</subject><subject>Parametric models</subject><subject>Population growth</subject><subject>Population size</subject><subject>Sine function</subject><subject>War</subject><issn>0070-3370</issn><issn>1533-7790</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1968</creationdate><recordtype>article</recordtype><sourceid>K30</sourceid><recordid>eNo9kFFPwjAQxxujiYjGL-BDgw--ML2227o9GgJIgpEEiY9LWTssjnW2XQzf3iro0z3c7-7-90PomsA9ZcAfKKRAIT9BPZIwFnGewynqAXCIGONwji6c2wJAHie0hz4W1rhWWe33Q_wm7BDPdju9scJr0wyxaCQejLrad1bUAzwRpTfWYd3gZyNVrZsNXjXaK4mXXnjl8MK0Xf07jKfWfPl3vNRNqTAJMS7RWSVqp66OtY9Wk_Hr6Cmav0xno8d5VFKIfUQIz1Ihy3xdrrkq17QSilJBcyUEyysecwWZIiG-lCmtSJLJRJIqlTRNaRInrI9uD3tbaz475XyxNZ1twsmC0JzTjAUyUHcHqgwGnFVV0Vq9E3ZfECh-TBZHk4G8OZBbF77_x_7a37mGbUw</recordid><startdate>19680101</startdate><enddate>19680101</enddate><creator>Diamantides, N. D.</creator><general>The Population Association of America</general><general>Population Association of America</general><scope>AAYXX</scope><scope>CITATION</scope><scope>FUVTR</scope><scope>HQAFP</scope><scope>K30</scope><scope>PAAUG</scope><scope>PAWHS</scope><scope>PAWZZ</scope><scope>PAXOH</scope><scope>PBHAV</scope><scope>PBQSW</scope><scope>PBYQZ</scope><scope>PCIWU</scope><scope>PCMID</scope><scope>PCZJX</scope><scope>PDGRG</scope><scope>PDWWI</scope><scope>PETMR</scope><scope>PFVGT</scope><scope>PGXDX</scope><scope>PIHIL</scope><scope>PISVA</scope><scope>PJCTQ</scope><scope>PJTMS</scope><scope>PLCHJ</scope><scope>PMHAD</scope><scope>PNQDJ</scope><scope>POUND</scope><scope>PPLAD</scope><scope>PQAPC</scope><scope>PQCAN</scope><scope>PQCMW</scope><scope>PQEME</scope><scope>PQHKH</scope><scope>PQMID</scope><scope>PQNCT</scope><scope>PQNET</scope><scope>PQSCT</scope><scope>PQSET</scope><scope>PSVJG</scope><scope>PVMQY</scope><scope>PZGFC</scope></search><sort><creationdate>19680101</creationdate><title>Prosperity, War, Immigration, and "Cultural" Factors in Modeling United States Population Growth Since 1790</title><author>Diamantides, N. D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c204t-11786adc9bcb7ecb2fae22a29eaa39f747e08e1452dd62f158d5d1f6d26625453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1968</creationdate><topic>Autocorrelation</topic><topic>Censuses</topic><topic>Demography</topic><topic>Differential equations</topic><topic>Gross national product</topic><topic>Parametric models</topic><topic>Population growth</topic><topic>Population size</topic><topic>Sine function</topic><topic>War</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Diamantides, N. D.</creatorcontrib><collection>CrossRef</collection><collection>Periodicals Index Online Segment 06</collection><collection>Periodicals Index Online Segment 23</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - West</collection><collection>Primary Sources Access (Plan D) - International</collection><collection>Primary Sources Access & Build (Plan A) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Midwest</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Northeast</collection><collection>Primary Sources Access (Plan D) - Southeast</collection><collection>Primary Sources Access (Plan D) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Southeast</collection><collection>Primary Sources Access (Plan D) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - UK / I</collection><collection>Primary Sources Access (Plan D) - Canada</collection><collection>Primary Sources Access (Plan D) - EMEALA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - International</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - International</collection><collection>Primary Sources Access (Plan D) - West</collection><collection>Periodicals Index Online Segments 1-50</collection><collection>Primary Sources Access (Plan D) - APAC</collection><collection>Primary Sources Access (Plan D) - Midwest</collection><collection>Primary Sources Access (Plan D) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Canada</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - EMEALA</collection><collection>Primary Sources Access & Build (Plan A) - APAC</collection><collection>Primary Sources Access & Build (Plan A) - Canada</collection><collection>Primary Sources Access & Build (Plan A) - West</collection><collection>Primary Sources Access & Build (Plan A) - EMEALA</collection><collection>Primary Sources Access (Plan D) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - Midwest</collection><collection>Primary Sources Access & Build (Plan A) - North Central</collection><collection>Primary Sources Access & Build (Plan A) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - Southeast</collection><collection>Primary Sources Access (Plan D) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - APAC</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - MEA</collection><jtitle>Demography</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Diamantides, N. D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prosperity, War, Immigration, and "Cultural" Factors in Modeling United States Population Growth Since 1790</atitle><jtitle>Demography</jtitle><date>1968-01-01</date><risdate>1968</risdate><volume>5</volume><issue>1</issue><spage>268</spage><epage>305</epage><pages>268-305</pages><issn>0070-3370</issn><eissn>1533-7790</eissn><abstract>The growth of the United States population since 1790 can be modeled in terms of a nonlinear differential equation with time-dependent coefficients. The growth process represented by the model is subject to the effects of immigration, war, prosperity, and a so-called "cultural" factor. Specifically, the equation assumes that the rate of growth for a particular year is the result of positive factors' working against limiting factors. The positive factors comprise (1) a term proportional to the population size, p, for that particular year, and (2) a term equal to the immigrant population, p m ', for the same year. The limiting factors are all proportional to the square of the present population size, p 2 and comprise a war term, w, that aids the growth-limiting process; a prosperity term, ε g ', that inhibits the limiting process; and a culture term C, that supports the limiting process, too. The term, w, is taken to be proportional to the wartime size of the country's armed forces, assuming that the war effects on population growth of a land faced with either the immediate prospect or the reality of armed conflict include both the casualties and the disruption of family life and planning of those directly involved. The term ε g ' is intended to be a measure of the general prosperity level. It is taken to be proportional to the ups and downs of the GNP, above or below a smooth trend line, the latter being found by curve-fitting a growth curve to the actual GNP data. Finally, the culture term, C, is assumed to vary with time, but not to be tied explicitly to known environmental, social, or other causes. It is probably connected to age distribution within the population, average age of partners of first marriages, number of children per woman of childbearing age, advances in medicine, the set of prevailing values, the trend of family planning, and so on. The time history of C emerging from the computer-based optimization of the model shows a downward trend. The use of the word "cultural" leaves something to be desired, since such phenomena as war, prosperity, and immigration excluded from C are nevertheless products of culture. With the analytical form of the differential equation describing population growth set up in this way, all proportionality constants (parameters) involved were determined by means of a digital computer and on the basis of an optimization process which utilized the actual data of population size p * over the period 1790-1965. The residual (p * -p) of this optimization or curve-fitting process was further examined through its autocorrection function, for additional deterministic components which were not accounted for by the model up to this point. The auto-correlation function provides a measure of the dependence of the population size p * for any year upon past values of p * ; it has the distinct feature of lifting any regular pattern possibly present in the data above the level of random fluctuations. The autocorrelation function of the residual (p * -p) did indicate the presence of a periodic component with a period of about sixty-five years. Accordingly, a periodic term of the same period was included in the cultural factor C, and the model was reoptimized. This resulted in a substantial reduction of the residual. A similar probing of the prosperity term, ε g , indicates the presence of a period one-half as long.</abstract><cop>Chicago, Ill</cop><pub>The Population Association of America</pub><doi>10.2307/2060209</doi><tpages>38</tpages></addata></record> |
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subjects | Autocorrelation Censuses Demography Differential equations Gross national product Parametric models Population growth Population size Sine function War |
title | Prosperity, War, Immigration, and "Cultural" Factors in Modeling United States Population Growth Since 1790 |
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